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针对人工室内环境的同时定位与构图(SLAM)问题,将元胞自动机(CA)引入到传统SLAM算法的迭代过程,建立“SLAM-CA生长-重定位”的闭环作用机制.利用室内规则环境的特性,以及大多数室内机器人应用领域已知先验地图的特点,对室内SLAM问题开展针对性的研究.通过仿真与实验证明,针对人工室内环境,该算法使得墙壁、出入口与直角特征更加明显,“穿墙”现象得到一定程度解决,改善了构图效果,提高了定位精度和路径规划可行性.
In order to solve the problem of Simultaneous Localization and Composition (SLAM) of indoor indoor environment, Cellular Automata (CA) is introduced into the iterative process of traditional SLAM algorithm to establish a closed-loop mechanism of “SLAM-CA growth- relocation” The characteristics of regular environment and the characteristics of known a priori maps in the field of most indoor robot applications, the author studies the indoor SLAM problem in detail.It is proved by simulation and experiment that for artificial indoor environment, the algorithm makes the wall, More obviously, the phenomenon of “penetrating the wall ” has been solved to some extent, the composition effect is improved, the positioning accuracy and the feasibility of the path planning are improved.